Creating ACIS RMFs with mkacisrmf

The tool mkacisrmf creates an RMF for an
ACIS imaging - or zeroth-order grating - observation with the
newest calibration available.
It replaces - for most cases - the
mkrmf tool.
We describe below when
mkacisrmf should be used, and further
instructions on how to run this
tool are given in the
mkacisrmf help file.

There is TGAIN calibration for all GRADED mode data, but CTI
correction for the front-illuminated chips only.

acisD2000-01-29gain_ctiN0006.fits

Note that any file since version 4 is "good enough" for use
with mkacisrmf.

-110 °C Data

For data taken at the -110 °C focal plane
temperature on the back-illuminated chips (ACIS-S1 and
S3), the appropriate gain file is automatically selected
when acis_process_events is run. The
TGAIN correction must also be
applied when reprocessing the data; there is no CTI available for -110 °C.

acisD1999-09-16gainN0006.fits

Analysis for the -110 °C front-illuminated chips must still
be done with mkrmf.

If the input file contains -110 °C data and has the
CTI-correction applied but the source is actually on a
front-illuminated chip, mkacisrmf fails with an
error:

Sherpa allows you to use different energy
grids for your ARF and RMF files, but XSpec does
not. XSpec will still run if the grids
do not match, but it issues a warning and sets all values
in the ARF to unity (1).

There are two approaches to creating an ARF-RMF pair with
the same gridding: Match an existing ARF or Create the RMF
first.

Match an existing ARF

If the specextract script was
used, you already have an ARF file for the data. Rather
than remake both the RMF and ARF, get the grid
information from the history in the ARF file.
The value of the parameter can be read from
the screen or extracted using the
action=pset
parameter, as shown below:

Since mkacisrmf can change the requested grid
to match the calibration data, create the RMF
first and then use it to define the energy grid when
creating the ARF. This will work for both
mkarf and mkwarf:

The mkacisrmf tool contains all the
functionality of the previous tool mkrmf. Unlike its
predecessor, however, mkacisrmf separates the RMF
calculation process into two components: an "ideal" component
which describes the CCD spectral response prior to the effects
of Charge Transfer Inefficiency
(CTI), and a spatially varying component which
incorporates the changes in the response produced by CTI.

This new method was motivated primarily by a desire to provide a
more rapid means of developing ACIS response calibration
products. Accompanying the new tool is a new CCD analysis
reference data (ARD) file which describes both the ideal
response and the spatial variation produced by CTI. In contrast
to traditional CCD FEFs, the CTI-induced spatial variations can
be generated directly from numerical simulations of the CCD
response obviating the need for laborious fitting at each
position on the CCD. This human-intensive fitting was the
primary bottleneck in generating ACIS FEFs. Once the "scatter
matrix", describing the spatial variations, has been generated
automatically, small scale adjustments are included to account
for differences between the simulated response and the actual
CCD response as measured using data from the onboard calibration
source.

The algorithm contained in mkacisrmf is based upon the
the algorithm in the calcrmf2 by Alexey Vikhlinin,
which is described in the memo "Updates
to the RMF model in the ACIS FI CCDs" (PDF). The CIAO
tool is essentially a direct translation of this prototype code
and includes a number of enhancements including an improved
interpolation scheme to calculate the response at intermediate
energies between the available calibration points. All
functionality of the previous tool mkrmf is available
including the ability to produce weighted response matrices for
arbitrary spatial regions.